A mobile base station is a radio and baseband processing system connecting the end mobile user to the mobile network. The base station may be distributed geographically in main-remote configuration or centralized with radio and baseband processing collocated.
Mobile base stations are typically connected via fixed transport links such as microwave, fiber, or DSL copper links. The act of transmitting data from the base station via possibly other base stations and aggregation points to the mobile core network is referred to as backhauling or radio access network transport. The network of transport links, base stations, and any other intermediary node before the mobile core network is referred to as the radio access network.
The selected backhauling architecture and deployed transport technology will vary depending on a particular deployment scenario. In a rural area, base station density may be less than in an urban area because of different requirements on network capacity. In rural areas, microwave may be a better choice of transport technology because the greater ability to avoid line of sight obstacles in those areas.
The base stations in radio access networks in technologies like GSM, see reference [1], UMTS, see ref. [2], and LTE, see ref. [3] are traditionally configured to be always on and are logically separated from the transport links that connect them together. Base stations are logically connected to the mobile core and, depending on technology, other base stations or subsystems.
Self-Organizing Networks, abbreviated SON, see reference [4], encompasses a set of features for 3GPP networks covering self-healing, self-optimization, and self-configuration of mobile networks. Self-healing targets provide automatic repair of network malfunctions, self-optimization automatic optimization of network resources, and self-configuration automatic, a.k.a. zero-touch, deployments.
The inflexibility of not scaling provisioned transport capacity after actual mobile user demand generates excess power. In a perfect network, energy consumption continuously aligns with the transport throughput requirements. When mobile subscriber activity decreases, then the provisioned transport capacity and also the power should be real-time adapted.
Today the main approaches to managing transport capacity in mobile networks are technology-specific local optimization, e.g. adaptive modulation, and manual control, e.g. via a network management system.
Local optimization may result in sub-optimal results. Manual control may be labor intensive and is not dynamic enough. For heterogeneous network deployments, the employed management system will also have to collect and process significantly more data as the number of data-reporting nodes may hundredfold.